Field of the Invention
The present disclosure relates to a method of efficiently allocating resources by analyzing a job history in a cloud computing system of a high-throughput computing field, and an apparatus used therefor.
Description of the Prior Art
In the computational science field, there are various computing paradigms according to application characteristics thereof. Further, the computing paradigms are approximately classified into High-Performance Computing (HPC), High-Throughput Computing (HTC), Many-Tasks Computing (MTC), etc. Although various researches on optimizing a performance of each paradigm have been conducted, an optimization technology suitable for a computing technology being rapidly changed is still required. In particular, the HTC corresponds to a paradigm which is actively adopted and utilized in the bioinformatics field, the new drug discovery field and the high-energy physics field, and a technology of optimizing and improving the performance of the HTC is required more and more. Since the HTC is mainly consisting of a large amount of tasks and commonly uses a technology such as parameter sweeping, when a large number of job histories are properly analyzed, a relationship between the performance of the application and the job properties can be identified, and the identified characteristic can be applied to various distributed computing technologies to make computing efficient.
Meanwhile, with the development of cloud computing, researchers of various science fields can receive a super computer which is essential to research, through an on-demand service, and research environments have been expanded as it becomes possible to expand dynamic resources. In this way, a science cloud has received attention as a new research environment paradigm in various recent science fields. However, since it is difficult to configure a rapid and dynamic virtual task space suitably for the demand of a user, it is considered important that a proper experimental environment considering application characteristics is configured before the execution of tasks. In addition, a scheduling mechanism which provides a virtual machine which secures a performance at an optimum level is also required.